Nonpharmacological interventions on glycated haemoglobin in youth with type 1 diabetes: a Bayesian network meta-analysis.

The available evidence on the impact of specific non-pharmacological interventions on glycaemic control is currently limited. Consequently, there is a need to determine which interventions could provide the most significant benefits for the metabolic health of young individuals with type 1 diabetes mellitus. The aim of this study was to identify optimal nonpharmacological interventions on glycaemic control, measured by glycated haemoglobin (HbA1c), in children and adolescents with type 1 diabetes. Systematic searches were conducted in PubMed, Web of Science, Scopus, and SPORTDiscus from inception to July 1, 2023. Randomised clinical trials (RCT) investigating nonpharmacological interventions (e.g., physical activity, nutrition, and behavioural therapies) were included. Primary outcome was change in HbA1c levels. Secondary outcome was change in daily insulin dose requirement. Seventy-four RCT with 6,815 participants (49.43% girls) involving 20 interventions were analysed using a network meta-analysis. Most interventions showed greater efficacy than standard care. However, multicomponent exercise, which includes aerobic and strength training (n = 214, standardised mean difference [SMD] =- 0.63, 95% credible interval [95% CrI] - 1.09 to - 0.16) and nutritional supplements (n = 146, SMD =- 0.49, - 0 .92 to - 0.07) demonstrated the greatest HbA1c reductions. These interventions also led to the larger decreases in daily insulin needs (n = 119, SMD =- 0.79, 95% CrI -  1.19 to - 0.34) and (n = 57, SMD =- 0.62, 95% CrI -  1.18 to - 0.12, respectively). The current study underscores non-pharmacological options such as multicomponent exercise and nutritional supplements, showcasing their potential to significantly improve HbA1c in youth with type 1 diabetes. Although additional research to confirm their efficacy is required, these approaches could be considered as potential adjuvant therapeutic options in the management of type 1 diabetes among children and adolescents.

Association between HLA alleles and haplotypes with age at diagnosis of type 1 diabetes in an admixed Brazilian population: A nationwide study.

To investigate the potential relationship between HLA alleles and haplotypes and the age at diagnosis of type 1 diabetes (T1DAgeD) in an admixed Brazilian population. This nationwide study was conducted in public clinics across 12 Brazilian cities. We collected demographic and genetic data from 1,600 patients with T1D. DNA samples were utilised to determine genomic ancestry (GA) and perform HLA typings for DRB1, DQA1 and DQB1. We explored allele and haplotype frequencies and GA in patients grouped by T1DAgeD categories (<6 years, ≥6-<11 years, ≥11-<19 years and ≥19 years) through univariate and multivariate analyses and primary component analyses. Additionally, we considered self-reported colour-race and identified a familiar history of T1D in first-degree relatives. The homozygosity index for DRB1~DQA1~DQB1 haplotypes exhibited the highest variation among T1DAgeD groups, and the percentages of Sub-Saharan African and European ancestries showed opposite trends in principal component analysis (PCA) analyses. Regarding the association of alleles and haplotypes with T1DAgeD, risk alleles such as HLA-DQB1*03:02g, -DQA1*03:01g, -02:01g, DRB1*04:05g and -04:02g were more frequently observed in heterozygosity or homozygosity in T1D patients with an early disease onset. Conversely, alleles such as DRB1*07:01g, -13:03g, DQB1*06:02g and DQA1*02:01 were more prevalent in older T1D patients. The combination DR3/DR4.5 was significantly associated with early disease onset. However, gender, GA, familiar history of T1D and self-reported colour-race identity did not exhibit significant associations with the onset of T1D. It is worth noting that the very common risk haplotype DRB1*03:01g~DQA1*05:01g~DQB1*02:01g did not differentiate between T1DAgeD groups. In the admixed Brazilian population, the high-risk haplotype DRB1*04:05~DQA1*03:01~DQB1*03:02 was more prevalent in individuals diagnosed before 6 years of age. In contrast, the protective alleles DQA1*01:02g, DQB1*06:02g, DRB1*07:01g and DRB1*13:03g and haplotypes DRB1*13:03g~DQA1*05:01g~DQB1*03:01g and DRB1*16:02g~DQA1*01:02g~DQB1*05:02g were more frequently observed in patients diagnosed in adulthood. Notably, these associations were independent of factors such as sex, economic status, GA, familiar history of T1D and region of birth in Brazil. These alleles and haplotypes contribute to our understanding of the disease onset heterogeneity and may have implications for early interventions when detected in association with well-known genomic risk or protection factors for T1D.

High-Density Lipoprotein Particle Concentration and Size Predict Incident Coronary Artery Disease Events in a Cohort With Type 1 Diabetes.

BACKGROUND: The cholesterol efflux capacity of high density lipoprotein (HDL) is negatively associated with cardiovascular risk. Small HDL particles account almost quantitatively for cholesterol efflux capacity, perhaps mediated through efflux of cholesterol and outer leaflet plasma membrane phospholipids by ABCA1 (ATP binding cassette subfamily A member 1). People with type 1 diabetes are at increased coronary artery disease (CAD) risk despite normal HDL-cholesterol concentrations. We therefore tested the hypothesis that small HDL particles (HDL-P)-rather than HDL-cholesterol-predict incident CAD in type 1 diabetes. METHODS AND RESULTS: Incident CAD (CAD death, myocardial infarction, or coronary revascularization) was determined in 550 individuals with childhood-onset type 1 diabetes. HDL-P was quantified by calibrated ion mobility analysis and cholesterol efflux capacity was quantified with validated assays. During a median follow-up of 26 years, 36.5% of the participants developed incident CAD, for an incidence density of 181.3 per 10 000 person-years. In multivariable Cox models, neither HDL-cholesterol nor apolipoprotein A1 concentration was significantly associated with CAD risk. In contrast, higher extra-small HDL-P concentrations were significantly associated with decreased CAD risk (hazard ratio [HR], 0.26 [95% CI, 0.14-0.50]). Weaker associations were observed for total HDL-P (HR, 0.88 [95% CI, 0.83-0.93]), small HDL (HR, 0.83 [95% CI, 0.68-1.02]), medium HDL (HR, 0.79 [95% CI, 0.71-0.89]), and large HDL (HR, 0.72 [95% CI, 0.59-0.89]). Although cholesterol efflux capacity was negatively associated with incident CAD, this association was no longer significant after adjustment for total HDL-P. CONCLUSIONS: Lower concentrations of total HDL-P and HDL subpopulations were positively associated with incident CAD independently of HDL-cholesterol, apolipoprotein A1, and other common CVD risk factors. Extra-small HDL was a much stronger predictor of risk than the other HDLs. Our data are consistent with the proposal that extra-small HDL plays a critical role in cardioprotection in type 1 diabetes, mediated by macrophage cholesterol efflux by the ABCA1 pathway.

Protein glycation products associate with progression of kidney disease and incident cardiovascular events in individuals with type 1 diabetes.

BACKGROUND: Despite improved glycemic treatment, the impact of glycation on pathological consequences may persist and contribute to adverse clinical outcomes in diabetes. In the present study we investigated the association between serum protein glycation products and progression of kidney disease as well as incident major adverse cardiovascular events (MACE) in type 1 diabetes. METHODS: Fructosamine, advanced glycation end products (AGEs), and methylglyoxal-modified hydro-imidazolone (MG-H1) were measured from baseline serum samples in the FinnDiane study (n = 575). Kidney disease progression was defined as steep eGFR decline (> 3 mL/min/1.73 m2/year) or progression of albuminuria (from lower to higher stage of albuminuria). MACE was defined as acute myocardial infarction, coronary revascularization, cerebrovascular event (stroke), and cardiovascular death. RESULTS: Fructosamine was independently associated with steep eGFR decline (OR 2.15 [95% CI 1.16-4.01], p = 0.016) in the fully adjusted model (age, sex, baseline eGFR). AGEs were associated with steep eGFR decline (OR 1.58 per 1 unit of SD [95% CI 1.07-2.32], p = 0.02), progression to end-stage kidney disease (ESKD) (HR 2.09 per 1 unit of SD [95% CI 1.43-3.05], p < 0.001), and pooled progression (to any stage of albuminuria) (HR 2.72 per 1 unit of SD [95% CI 2.04-3.62], p < 0.001). AGEs (HR 1.57 per 1 unit of SD [95% CI 1.23-2.00], p < 0.001) and MG-H1 (HR 4.99 [95% CI 0.98-25.55], p = 0.054) were associated with incident MACE. MG-H1 was also associated with pooled progression (HR 4.19 [95% CI 1.11-15.89], p = 0.035). Most AGEs and MG-H1 associations were no more significant after adjusting for baseline eGFR. CONCLUSIONS: Overall, these findings suggest that protein glycation products are an important risk factor for target organ damage in type 1 diabetes. The data provide further support to investigate a potential causal role of serum protein glycation in the progression of diabetes complications.

A high-volume study on the impact of diabetes mellitus on clinical outcomes after surgical and percutaneous cardiac interventions.

BACKGROUND: Type I and type II diabetes mellitus (DM) patients have a higher prevalence of cardiovascular diseases, as well as a higher mortality risk of cardiovascular diseases and interventions. This study provides an update on the impact of DM on clinical outcomes, including mortality, complications and reinterventions, using data on percutaneous and surgical cardiac interventions in the Netherlands. METHODS: This is a retrospective, nearby nationwide study using real-world observational data registered by the Netherlands Heart Registration (NHR) between 2015 and 2020. Patients treated for combined or isolated coronary artery disease (CAD) and aortic valve disease (AVD) were studied. Bivariate analyses and multivariate logistic regression models were used to evaluate the association between DM and clinical outcomes both unadjusted and adjusted for baseline characteristics. RESULTS: 241,360 patients underwent the following interventions; percutaneous coronary intervention(N = 177,556), coronary artery bypass grafting(N = 39,069), transcatheter aortic valve implantation(N = 11,819), aortic valve replacement(N = 8,028) and combined CABG and AVR(N = 4,888). The incidence of DM type I and II was 21.1%, 26.7%, 17.8%, 27.6% and 27% respectively. For all procedures, there are statistically significant differences between patients living with and without diabetes, adjusted for baseline characteristics, at the expense of patients with diabetes for 30-days mortality after PCI (OR = 1.68; p <.001); 120-days mortality after CABG (OR = 1.35; p <.001), AVR (OR = 1.5; p <.03) and CABG + AVR (OR = 1.42; p =.02); and 1-year mortality after CABG (OR = 1.43; p <.001), TAVI (OR = 1.21; p =.01) and PCI (OR = 1.68; p <.001). CONCLUSION: Patients with DM remain to have unfavourable outcomes compared to nondiabetic patients which calls for a critical reappraisal of existing care pathways aimed at diabetic patients within the cardiovascular field.

Comparison of Bayesian approaches for developing prediction models in rare disease: application to the identification of patients with Maturity-Onset Diabetes of the Young.

BACKGROUND: Clinical prediction models can help identify high-risk patients and facilitate timely interventions. However, developing such models for rare diseases presents challenges due to the scarcity of affected patients for developing and calibrating models. Methods that pool information from multiple sources can help with these challenges. METHODS: We compared three approaches for developing clinical prediction models for population screening based on an example of discriminating a rare form of diabetes (Maturity-Onset Diabetes of the Young - MODY) in insulin-treated patients from the more common Type 1 diabetes (T1D). Two datasets were used: a case-control dataset (278 T1D, 177 MODY) and a population-representative dataset (1418 patients, 96 MODY tested with biomarker testing, 7 MODY positive). To build a population-level prediction model, we compared three methods for recalibrating models developed in case-control data. These were prevalence adjustment ("offset"), shrinkage recalibration in the population-level dataset ("recalibration"), and a refitting of the model to the population-level dataset ("re-estimation"). We then developed a Bayesian hierarchical mixture model combining shrinkage recalibration with additional informative biomarker information only available in the population-representative dataset. We developed a method for dealing with missing biomarker and outcome information using prior information from the literature and other data sources to ensure the clinical validity of predictions for certain biomarker combinations. RESULTS: The offset, re-estimation, and recalibration methods showed good calibration in the population-representative dataset. The offset and recalibration methods displayed the lowest predictive uncertainty due to borrowing information from the fitted case-control model. We demonstrate the potential of a mixture model for incorporating informative biomarkers, which significantly enhanced the model's predictive accuracy, reduced uncertainty, and showed higher stability in all ranges of predictive outcome probabilities. CONCLUSION: We have compared several approaches that could be used to develop prediction models for rare diseases. Our findings highlight the recalibration mixture model as the optimal strategy if a population-level dataset is available. This approach offers the flexibility to incorporate additional predictors and informed prior probabilities, contributing to enhanced prediction accuracy for rare diseases. It also allows predictions without these additional tests, providing additional information on whether a patient should undergo further biomarker testing before genetic testing.

Abnormal vascular thickness and stiffness in young adults with type 1 diabetes: new insights from cutting-edge ultrasound modalities.

BACKGROUND: Cardiovascular disease (CVD) remains the leading cause of morbidity and mortality in patients with Type 1 Diabetes (T1D). Early markers of CVD include increased carotid intima-media thickness (CIMT) and pulse wave velocity (PWV), but these existing ultrasound technologies show limited spatial and temporal resolution in young adults. The purpose of this study is to evaluate the utility of high-resolution ultrasound modalities, including high frequency ultrasound CIMT (hfCIMT) and ultrafast ultrasound PWV (ufPWV), in young adults with Type 1 Diabetes. METHODS: This is a prospective single-center observational cohort study including 39 participants with T1D and 25 age and sex matched controls. All participants underwent hfCIMT and ufPWV measurements. hfCIMT and ufPWV measures of T1D were compared with controls and associations with age, sex, BMI, A1c, blood pressure, and lipids were studied. RESULTS: Mean age was 24.1 years old in both groups. T1D had a greater body mass index (27.7 [5.7] vs 23.1 [3.2] kg/m2), LDL Cholesterol, and estimated GFR, and had a mean A1c of 7.4 [1.0] % (57 mmol/mol) and diabetes duration of 16.1 [3.7] years with 56% using insulin pumps. In T1D, hfCIMT was significantly increased as compared to controls (0.435 ± 0.06 mm vs 0.379 ± 0.06 mm respectively, p < 0.01). ufPWV measures were significantly increased in T1D (systolic foot PWV: 5.29 ± 0.23 m/s vs 5.50 ± 0.37 m/s, p < 0.01; dicrotic notch PWV = 7.54 ± 0.46 m/s vs 7.92 ± 0.41 m/s, p < 0.01). Further, there was an impact of A1c-measured glycemia on hfCIMT, but this relationship was not seen with ufPWV. No significant statistical correlations between hfCIMT and ufPWV measures in either T1D or healthy controls were observed. CONCLUSION: Young adults with T1D present with differences in arterial thickness and stiffness when compared with controls. Use of novel high-resolution ultrasound measures describe important relationships between early structural and vascular pathophysiologic changes and are promising tools to evaluate pre-clinical CVD risk in youth with T1D. TRIAL REGISTRATION: ISRCTN91419926.

Challenges in autoimmune polyendocrine syndrome type 2 with the full triad induced by anti-programmed cell death 1: a case report and review of the literature.

Background: Immune checkpoint inhibitors (ICPis) induce autoimmune diseases, including autoimmune polyendocrine syndrome type 2 (APS-2), which is defined as a combination of at least two of the following endocrinopathies: autoimmune thyroid disease, type 1 diabetes, and Addison's disease. Cases with the full triad are rare. We present a case of an elderly woman who developed APS-2 with the complete triad shortly after starting anti-programmed cell death 1 (anti-PD1) treatment and review the related literature. Case: A 60-year-old woman, without any personal or family history of autoimmune and endocrine diseases, started the immunotherapy of anti-PD1 (camrelizumab) for squamous cell carcinoma of the urethral meatus. She developed primary hypothyroidism with elevated antibodies to thyroid peroxidase and thyroglobulin after 25 weeks of treatment, and developed primary adrenal insufficiency with adrenal crisis and fulminant type 1 diabetes with ketoacidosis after 45 weeks. Therefore, this patient met the diagnosis of APS-2 and was given multiple hormone replacement including glucocorticoid, levothyroxine and insulin therapy. Continuous improvement was achieved through regular monitoring and titration of the dosage. Conclusions: Different components of APS-2 may appear at different time points after anti-PD1 administration, and can be acute and life-threatening. A good prognosis can be obtained by appropriate replacement with multiple hormones. Insights: With the clinical application of ICPis to APS-2, the complexity of its treatment should be paid enough attention.

Childhood screening for type 1 diabetes comparing automated multiplex Antibody Detection by Agglutination-PCR (ADAP) with single plex islet autoantibody radiobinding assays.

BACKGROUND: Two or more autoantibodies against either insulin (IAA), glutamic acid decarboxylase (GADA), islet antigen-2 (IA-2A) or zinc transporter 8 (ZnT8A) denote stage 1 (normoglycemia) or stage 2 (dysglycemia) type 1 diabetes prior to stage 3 type 1 diabetes. Automated multiplex Antibody Detection by Agglutination-PCR (ADAP) assays in two laboratories were compared to single plex radiobinding assays (RBA) to define threshold levels for diagnostic specificity and sensitivity. METHODS: IAA, GADA, IA-2A and ZnT8A were analysed in 1504 (54% females) population based controls (PBC), 456 (55% females) doctor's office controls (DOC) and 535 (41% females) blood donor controls (BDC) as well as in 2300 (48% females) patients newly diagnosed (1-10 years of age) with stage 3 type 1 diabetes. The thresholds for autoantibody positivity were computed in 100 10-fold cross-validations to separate patients from controls either by maximizing the χ2-statistics (chisq) or using the 98th percentile of specificity (Spec98). Mean and 95% CI for threshold, sensitivity and specificity are presented. FINDINGS: The ADAP ROC curves of the four autoantibodies showed comparable AUC in the two ADAP laboratories and were higher than RBA. Detection of two or more autoantibodies using chisq showed 0.97 (0.95, 0.99) sensitivity and 0.94 (0.91, 0.97) specificity in ADAP compared to 0.90 (0.88, 0.95) sensitivity and 0.97 (0.94, 0.98) specificity in RBA. Using Spec98, ADAP showed 0.92 (0.89, 0.95) sensitivity and 0.99 (0.98, 1.00) specificity compared to 0.89 (0.77, 0.86) sensitivity and 1.00 (0.99, 1.00) specificity in the RBA. The diagnostic sensitivity and specificity were higher in PBC compared to DOC and BDC. INTERPRETATION: ADAP was comparable in two laboratories, both comparable to or better than RBA, to define threshold levels for two or more autoantibodies to stage type 1 diabetes. FUNDING: Supported by The Leona M. and Harry B. Helmsley Charitable Trust (grant number 2009-04078), the Swedish Foundation for Strategic Research (Dnr IRC15-0067) and the Swedish Research Council, Strategic Research Area (Dnr 2009-1039). AL was supported by the DiaUnion collaborative study, co-financed by EU Interreg ÖKS, Capital Region of Denmark, Region Skåne and the Novo Nordisk Foundation.

[Diabetes-related skin lesions : a frequently underdiagnosed problem]. / Lésions cutanées liées au diabète : une problématique souvent sous-diagnostiquée.

Skin disorders are common in diabetes, affecting both patients with type 1 and type 2 diabetes. These cutaneous manifestations can be classified into three categories: dermatoses associated with the presence of diabetes, cutaneous complications of diabetes (acute and chronic) and dermatoses linked to antidiabetic treatments. These conditions vary considerably in terms of severity (from insignificant cosmetic problems to life-threatening) and prevalence (from relatively frequent to rare). Despite the high prevalence of diabetes and associated skin disorders, the dermatological manifestations of diabetes are generally neglected and often under-diagnosed. Failure to diagnose and treat skin disorders at an early stage can lead to clinical worsening, whereas early detection and treatment can reduce the risk of serious complications.

Chez les personnes atteintes d'un diabète de type 1 ou 2, les atteintes cutanées sont fréquentes. Elles peuvent être classées en trois catégories : les dermatoses associées à la présence du diabète, ses complications cutanées (aiguës et chroniques) et les dermatoses liées aux traitements antidiabétiques. Ces atteintes varient considérablement en gravité (allant de préoccupations esthétiques banales à potentiellement mortelles) et en prévalence (relativement fréquentes à rares). Malgré la prévalence élevée du diabète et des atteintes cutanées associées, les manifestations dermatologiques sont généralement négligées et souvent sous-diagnostiquées. L'absence de diagnostic et de traitement à un stade précoce peut entraîner une aggravation clinique dermatologique. La détection et le traitement précoces de ces atteintes peuvent réduire le risque de complications graves.

[Diabetic gastroparesis and type 1 diabetes]. / Gastroparésie diabétique et diabète de type 1.

Gastroparesis is a rare and late microvascular complication, but a significant one of diabetes. Defined by a slowing of gastric emptying, this condition manifests with nonspecific gastrointestinal symptoms, including nausea, vomiting, abdominal pain, postprandial fullness, and early satiety. Faced with such a clinical presentation, it is often challenging to diagnose gastroparesis. In this article, we discuss the diagnostic procedures, as well as therapeutic approaches and management of the disease.

La gastroparésie est une complication microvasculaire rare et tardive, mais conséquente, du diabète. Définie par un ralentissement de la vidange gastrique, cette pathologie se présente sous la forme de symptômes gastro-intestinaux aspécifiques incluant des nausées, des vomissements, des douleurs abdominales, une sensation de réplétion postprandiale et une satiété précoce. Face à une présentation clinique de ce type, il est souvent difficile de poser le diagnostic de gastroparésie. Dans cet article, nous évoquons donc les examens complémentaires permettant de poser le diagnostic, ainsi que les propositions thérapeutiques et la prise en charge de la maladie.

[Towards a new way to classify diabetes mellitus]. / Vers une nouvelle classification des diabètes.

Precision medicine makes it possible to classify patients into groups on the basis of molecular and genetic biomarkers, as well as clinical characteristics, in order to optimize therapeutic response. For example, several types of type 2 diabetes seem to coexist with classic insulin-dependent, autoimmune type 1 diabetes : diabetes with insulinopenia (generally severe), diabetes linked to aging or obesity (less severe), and diabetes with insulin resistance, whose patients will be those with the most numerous complications, notably macrovascular. In this article, we examine the possibilities offered by this new classification of diabetes with a view to personalized medicine.

La médecine de précision permet de classer les patients en groupes sur la base de biomarqueurs moléculaires et génétiques ainsi que de caractéristiques cliniques afin d'optimiser la réponse thérapeutique. Ainsi, plusieurs types de diabètes de type 2 semblent coexister à côté du classique diabète de type 1, insulinoprive et avec auto-immunité : des diabètes avec insulinopénie (généralement sévères), des diabètes liés au vieillissement ou à l'obésité (moins sévères), et des diabètes avec insulinorésistance dont les patients porteurs seront ceux qui auront le plus de complications, en particulier macrovasculaires. Dans cet article, nous abordons les possibilités offertes par cette nouvelle classification du diabète vers la perspective d'une médecine personnalisée.

Prediction of progression to type 1 diabetes with dynamic biomarkers and risk scores.

Identifying biomarkers of functional ß-cell loss is an important step in the risk stratification of type 1 diabetes. Genetic risk scores (GRS), generated by profiling an array of single nucleotide polymorphisms, are a widely used type 1 diabetes risk-prediction tool. Type 1 diabetes screening studies have relied on a combination of biochemical (autoantibody) and GRS screening methodologies for identifying individuals at high-risk of type 1 diabetes. A limitation of these screening tools is that the presence of autoantibodies marks the initiation of ß-cell loss, and is therefore not the best biomarker of progression to early-stage type 1 diabetes. GRS, on the other hand, represents a static biomarker offering a single risk score over an individual's lifetime. In this Personal View, we explore the challenges and opportunities of static and dynamic biomarkers in the prediction of progression to type 1 diabetes. We discuss future directions wherein newer dynamic risk scores could be used to predict type 1 diabetes risk, assess the efficacy of new and emerging drugs to retard, or prevent type 1 diabetes, and possibly replace or further enhance the predictive ability offered by static biomarkers, such as GRS.

Equitable implementation of a precision digital health program for glucose management in individuals with newly diagnosed type 1 diabetes.

Few young people with type 1 diabetes (T1D) meet glucose targets. Continuous glucose monitoring improves glycemia, but access is not equitable. We prospectively assessed the impact of a systematic and equitable digital-health-team-based care program implementing tighter glucose targets (HbA1c < 7%), early technology use (continuous glucose monitoring starts <1 month after diagnosis) and remote patient monitoring on glycemia in young people with newly diagnosed T1D enrolled in the Teamwork, Targets, Technology, and Tight Control (4T Study 1). Primary outcome was HbA1c change from 4 to 12 months after diagnosis; the secondary outcome was achieving the HbA1c targets. The 4T Study 1 cohort (36.8% Hispanic and 35.3% publicly insured) had a mean HbA1c of 6.58%, 64% with HbA1c < 7% and mean time in the range (70-180 mg dl-1) of 68% at 1 year after diagnosis. Clinical implementation of the 4T Study 1 met the prespecified primary outcome and improved glycemia without unexpected serious adverse events. The strategies in the 4T Study 1 can be used to implement systematic and equitable care for individuals with T1D and translate to care for other chronic diseases. ClinicalTrials.gov registration: NCT04336969 .

Previously undiagnosed genetic disease in adult patient with hepatic masses and reported history of congenital hyperinsulinism.

Glycogen storage disease type 1A (GSD1A), also known as Von Gierke's disease, is a rare autosomal recessive disorder affecting glycogen metabolism in the liver. It most commonly presents in infancy with hypoglycaemia and failure to thrive, but cases have been reported as undiagnosed until adulthood. A woman in her early 20s with diabetes mellitus presented with right upper quadrant pain and was found to have several haemorrhagic hepatic adenomas. This patient had insulin-dependent diabetes since a pancreatectomy at age 9 months due to continued episodes of hypoglycaemia and suspected insulinoma. During the hospital stay, the hepatic adenomas were embolised, but significant lactic acidosis and hypoglycaemia continued. Further workup revealed a chronic lactic acid level, during several hospital stays, of above 5 mmol/L. After cytology of hepatic tissue ruled out hepatocellular carcinoma, the patient was discharged and recommended to follow-up for genetic testing, which confirmed the diagnosis of GSD1A.

Insulin sensitivity estimates and their longitudinal association with coronary artery disease in type 1 diabetes. Does it matter?

BACKGROUND: Insulin resistance and chronic kidney disease are both associated with increased coronary artery disease risk. Many formulae estimating glucose disposal rate in type 1 diabetes infer insulin sensitivity from clinical data. We compare associations and performance relative to traditional risk factors and kidney disease severity between three formulae estimating the glucose disposal rate and coronary artery disease in people with type 1 diabetes. METHODS: The baseline glucose disposal rate was estimated by three (Williams, Duca, and Januszewski) formulae in FinnDiane Study participants and related to subsequent incidence of coronary artery disease, by baseline kidney status. RESULTS: In 3517 adults with type 1 diabetes, during median (IQR) 19.3 (14.6, 21.4) years, 539 (15.3%) experienced a coronary artery disease event, with higher rates with worsening baseline kidney status. Correlations between the three formulae estimating the glucose disposal rate were weak, but the lowest quartile of each formula was associated with higher incidence of coronary artery disease. Importantly, only the glucose disposal rate estimation by Williams showed a linear association with coronary artery disease risk in all analyses. Of the three formulae, Williams was the strongest predictor of coronary artery disease. Only age and diabetes duration were stronger predictors. The strength of associations between estimated glucose disposal rate and CAD incidence varied by formula and kidney status. CONCLUSIONS: In type 1 diabetes, estimated glucose disposal rates are associated with subsequent coronary artery disease, modulated by kidney disease severity. Future research is merited regarding the clinical usefulness of estimating the glucose disposal rate as a coronary artery disease risk factor and potential therapeutic target.

Screening for diabetic peripheral neuropathy at community pharmacies in Slovakia.

AIM: To identify diabetic patients with a potential risk of developing diabetic peripheral neuropathy (DPN) in community pharmacies in Slovakia using a modified Michigan Neuropathy Screening Instrument questionnaire (MNSIq-12). METHODS: This cross-sectional study enrolled 703 patients with type 1 and type 2 diabetes mellitus who had not been diagnosed with DPN. The study took place in selected community pharmacies across Slovakia in October 2019. The MNSIq-12 was administered by pharmacy students, and a Michigan score <1.5 was considered risky. The groups divided based on the Michigan score were compared in terms of duration of diabetes, age, body mass index (BMI), sex, weekly physical activity, level of education, and smoking. RESULTS: The risk of developing DPN was detected in 6.6% of respondents with type 1 diabetes and 13.4% with type 2 diabetes. Patients with both types of diabetes (38.2%; 67.0%) reported fatigue and heaviness in the legs as the most common clinical symptoms that may indicate the development of DPN. Those with a Michigan score <1.5 were older (P<0.0001), had a higher BMI (P<0.0001), a lower level of education (P=0.0020), and were less physically active (P<0.0001). Conclusion Approximately one-eighth of patients with diabetes who visited community pharmacies were potentially at risk for developing DPN. The modified MNSIq-12 was shown to be a simple, time-effective, and non-invasive indicative screening tool that can be applied in the environment of community pharmacies.